Back to guide/Education & Learning

Code Debugging

Tracing execution step by step reveals bugs that pattern-matching misses. Restating intent first ensures the model understands the goal before diagnosing the problem.

chain-of-thought-promptinglanguagecode_snippetexpected_behavior
Edit View
Prompt
Debug the following code. Do not just give the fix — walk through your reasoning so I understand the root cause.

Language: {{language}}
Code:
{{code_snippet}}

Expected behavior: {{expected_behavior}}
Actual behavior: {{actual_behavior}}

Debug step by step:
1. Read the code and restate what it's supposed to do
2. Trace through the execution mentally, noting variable states
3. Identify where the actual behavior diverges from expected
4. Explain the root cause of the bug
5. Provide the corrected code with comments on what changed

Variables to customize

{{language}}{{code_snippet}}{{expected_behavior}}{{actual_behavior}}

Why this prompt works

Tracing execution step by step reveals bugs that pattern-matching misses. Restating intent first ensures the model understands the goal before diagnosing the problem.

Save this prompt to your library

Organize, version, and access your best prompts across ChatGPT, Claude, and Cursor.

Related prompts

Sentiment Analysis

Requesting confidence and key phrases forces the model to justify its classification rather than guessing. The structured output format works zero-shot because sentiment analysis is well-understood by LLMs.

Key Information Extraction

Listing the exact fields to extract removes guesswork. The 'Not specified' instruction prevents hallucination when information is missing -- a common failure mode without this guardrail.

Question Answering with Source

Grounding the answer in source material and instructing the model to refuse when information is missing dramatically reduces hallucination -- the biggest risk in zero-shot Q&A.

Math Word Problem Reasoning

Explicit numbered steps force the model to decompose the problem rather than guessing. The verification step catches arithmetic errors before the final answer.